Hongluan Mao

719 total citations
22 papers, 458 citations indexed

About

Hongluan Mao is a scholar working on Molecular Biology, Cancer Research and Obstetrics and Gynecology. According to data from OpenAlex, Hongluan Mao has authored 22 papers receiving a total of 458 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 9 papers in Cancer Research and 6 papers in Obstetrics and Gynecology. Recurrent topics in Hongluan Mao's work include Endometrial and Cervical Cancer Treatments (4 papers), MicroRNA in disease regulation (4 papers) and Uterine Myomas and Treatments (4 papers). Hongluan Mao is often cited by papers focused on Endometrial and Cervical Cancer Treatments (4 papers), MicroRNA in disease regulation (4 papers) and Uterine Myomas and Treatments (4 papers). Hongluan Mao collaborates with scholars based in China. Hongluan Mao's co-authors include Peishu Liu, Yingxin Pang, Xuan Wei, Xinrui Zhao, Jing Xue, Rui Li, Liang Shen, Ruihan Liu, Zhe Zhao and Yu Wang and has published in prestigious journals such as Frontiers in Oncology, Journal of Translational Medicine and Frontiers in Genetics.

In The Last Decade

Hongluan Mao

22 papers receiving 453 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Hongluan Mao China 14 234 164 129 96 80 22 458
Joema Felipe Lima United States 10 264 1.1× 214 1.3× 242 1.9× 86 0.9× 40 0.5× 15 535
Lina Albitar United States 10 204 0.9× 99 0.6× 117 0.9× 51 0.5× 69 0.9× 12 374
Fanfei Kong China 15 422 1.8× 378 2.3× 151 1.2× 38 0.4× 62 0.8× 26 626
Betül T. Yesilyurt Belgium 8 184 0.8× 140 0.9× 194 1.5× 79 0.8× 42 0.5× 9 452
L. Edwards Australia 7 139 0.6× 73 0.4× 142 1.1× 104 1.1× 54 0.7× 7 363
Phil Rolland United Kingdom 10 190 0.8× 88 0.5× 229 1.8× 144 1.5× 137 1.7× 11 582
Laura M S Seeber Netherlands 7 255 1.1× 147 0.9× 83 0.6× 76 0.8× 62 0.8× 7 368
Eun Mi Je South Korea 12 254 1.1× 117 0.7× 79 0.6× 56 0.6× 63 0.8× 18 440
Kei Ihira Japan 15 556 2.4× 485 3.0× 107 0.8× 46 0.5× 64 0.8× 23 704
Rui Gou China 16 367 1.6× 248 1.5× 120 0.9× 54 0.6× 33 0.4× 28 547

Countries citing papers authored by Hongluan Mao

Since Specialization
Citations

This map shows the geographic impact of Hongluan Mao's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Hongluan Mao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hongluan Mao more than expected).

Fields of papers citing papers by Hongluan Mao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hongluan Mao. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Hongluan Mao. The network helps show where Hongluan Mao may publish in the future.

Co-authorship network of co-authors of Hongluan Mao

This figure shows the co-authorship network connecting the top 25 collaborators of Hongluan Mao. A scholar is included among the top collaborators of Hongluan Mao based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hongluan Mao. Hongluan Mao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Hou, Yue, Miao Li, Xue Han, et al.. (2023). The gene signature of tertiary lymphoid structures within ovarian cancer predicts the prognosis and immunotherapy benefit. Frontiers in Genetics. 13. 1090640–1090640. 19 indexed citations
2.
3.
Pang, Yingxin, Jing Zhao, Rui Li, et al.. (2022). The BRD4 inhibitor JQ1 suppresses tumor growth by reducing c-Myc expression in endometrial cancer. Journal of Translational Medicine. 20(1). 336–336. 34 indexed citations
4.
Ma, Xiaoxue, Jing Zhao, Xuan Wei, et al.. (2021). GABPA Expression in Endometrial Carcinoma: A Prognostic Marker. Disease Markers. 2021. 1–9. 4 indexed citations
5.
Zhang, Xue, et al.. (2021). Identification of Three Potential Prognostic Genes in Platinum-Resistant Ovarian Cancer via Integrated Bioinformatics Analysis. Cancer Management and Research. Volume 13. 8629–8646. 7 indexed citations
6.
Huang, Xueyao, Xuan Wei, Xue Zhang, et al.. (2021). Low Density Lipoprotein Receptor (LDLR) and 3-Hydroxy-3-Methylglutaryl Coenzyme a Reductase (HMGCR) Expression are Associated with Platinum-Resistance and Prognosis in Ovarian Carcinoma Patients. Cancer Management and Research. Volume 13. 9015–9024. 13 indexed citations
7.
Wei, Xuan, Juanjuan Shi, Xiaoxue Ma, et al.. (2021). Targeting ACLY Attenuates Tumor Growth and Acquired Cisplatin Resistance in Ovarian Cancer by Inhibiting the PI3K–AKT Pathway and Activating the AMPK–ROS Pathway. Frontiers in Oncology. 11. 642229–642229. 47 indexed citations
8.
Xu, Hui, Hongluan Mao, Xinrui Zhao, Yue Li, & Peishu Liu. (2020). MiR-29c-3p, a target miRNA of LINC01296, accelerates tumor malignancy: therapeutic potential of a LINC01296/miR-29c-3p axis in ovarian cancer. Journal of Ovarian Research. 13(1). 31–31. 16 indexed citations
9.
Zhang, Xiaolei, Tao Lu, Yanhui Ma, et al.. (2020). <p>Novel Nanocomplexes Targeting STAT3 Demonstrate Promising Anti-Ovarian Cancer Effects in vivo</p>. OncoTargets and Therapy. Volume 13. 5069–5082. 8 indexed citations
10.
Pang, Yingxin, Rui Li, Xuan Wei, et al.. (2019). <p>Akt/mTOR-Mediated Autophagy Confers Resistance To BET Inhibitor JQ1 In Ovarian Cancer</p>. OncoTargets and Therapy. Volume 12. 8063–8074. 30 indexed citations
11.
Li, Rui, Tianfeng Liu, Juanjuan Shi, et al.. (2019). ROR2 induces cell apoptosis via activating IRE1α/JNK/CHOP pathway in high-grade serous ovarian carcinoma in vitro and in vivo. Journal of Translational Medicine. 17(1). 428–428. 15 indexed citations
12.
Zhao, Xinrui, et al.. (2018). Prognostic roles of neutrophil to lymphocyte ratio and platelet to lymphocyte ratio in ovarian cancer: a meta-analysis of retrospective studies. Archives of Gynecology and Obstetrics. 297(4). 849–857. 69 indexed citations
13.
Ma, Congcong, Yu Zhang, Rui Li, Hongluan Mao, & Peishu Liu. (2017). Risk of parametrial invasion in women with early stage cervical cancer: a meta-analysis. Archives of Gynecology and Obstetrics. 297(3). 573–580. 19 indexed citations
14.
Wang, Yunxia, Peishu Liu, Xietong Wang, & Hongluan Mao. (2017). Role of X-linked inhibitor of apoptosis-associated factor-1 in vasculogenic mimicry in ovarian cancer. Molecular Medicine Reports. 16(1). 325–330. 8 indexed citations
15.
Mao, Hongluan, et al.. (2016). Can postoperative GnRH agonist treatment prevent endometriosis recurrence? A meta-analysis. Archives of Gynecology and Obstetrics. 294(1). 201–207. 28 indexed citations
16.
Pang, Yingxin, Hongluan Mao, Liang Shen, et al.. (2014). MiR-519d represses ovarian cancer cell proliferation and enhances cisplatin-mediated cytotoxicity in vitro by targeting XIAP. OncoTargets and Therapy. 7. 587–587. 50 indexed citations
17.
Mao, Hongluan, et al.. (2014). Conservative management of endometrial stromal sarcoma at stage III: A case report. Oncology Letters. 8(3). 1234–1236. 10 indexed citations
18.
Pang, Yingxin, et al.. (2014). Successful pregnancy following conservative management of low-grade endometrial stromal sarcoma: A case report. Oncology Letters. 7(4). 1039–1042. 17 indexed citations
19.
Zhang, Xiaolei, et al.. (2013). Inhibitory effects of STAT3 decoy oligodeoxynucleotides on human epithelial ovarian cancer cell growth in vivo. International Journal of Molecular Medicine. 32(3). 623–628. 25 indexed citations
20.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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